chr12.5652_chr12_107323353_107326282_+_2.R fitVsDatCorrelation=0.857956700535285 cont.fitVsDatCorrelation=0.240986244837155 fstatistic=9375.63187039961,66,1014 cont.fstatistic=2615.82120789917,66,1014 residuals=-0.756105969693257,-0.0976802911831769,-0.00660551257095914,0.0929578336270759,1.02834514260343 cont.residuals=-0.751856357740316,-0.233646467804912,-0.0232068666973320,0.198589172942539,1.82122803075999 predictedValues: Include Exclude Both chr12.5652_chr12_107323353_107326282_+_2.R.tl.Lung 76.9279906093344 79.5129610137185 89.7229245791703 chr12.5652_chr12_107323353_107326282_+_2.R.tl.cerebhem 83.9443290421976 48.5514851838824 113.191837734296 chr12.5652_chr12_107323353_107326282_+_2.R.tl.cortex 91.6416833510213 55.1985695794084 117.822378483233 chr12.5652_chr12_107323353_107326282_+_2.R.tl.heart 79.2626191822505 62.8112380495754 88.8734802372681 chr12.5652_chr12_107323353_107326282_+_2.R.tl.kidney 68.7087871205086 72.8496685218247 77.7587532818942 chr12.5652_chr12_107323353_107326282_+_2.R.tl.liver 66.5439774911822 64.9260744571695 70.6286746610707 chr12.5652_chr12_107323353_107326282_+_2.R.tl.stomach 68.2622930751109 59.0781518302177 78.882960307489 chr12.5652_chr12_107323353_107326282_+_2.R.tl.testicle 67.0760605024901 62.764513109975 71.659351503006 diffExp=-2.58497040438408,35.3928438583151,36.4431137716129,16.4513811326751,-4.14088140131611,1.61790303401267,9.18414124489318,4.31154739251511 diffExpScore=1.12748086601273 diffExp1.5=0,1,1,0,0,0,0,0 diffExp1.5Score=0.666666666666667 diffExp1.4=0,1,1,0,0,0,0,0 diffExp1.4Score=0.666666666666667 diffExp1.3=0,1,1,0,0,0,0,0 diffExp1.3Score=0.666666666666667 diffExp1.2=0,1,1,1,0,0,0,0 diffExp1.2Score=0.75 cont.predictedValues: Include Exclude Both Lung 83.6095438636873 78.567771176496 78.932590397911 cerebhem 78.6301964756377 80.8391085413456 77.5076169634794 cortex 81.7387391299767 88.8879474534191 77.2222557648948 heart 81.5547209107386 94.0748574568543 82.9856737461127 kidney 78.4052453891734 86.910952258785 86.4788041420818 liver 82.6854594603731 79.301710840296 79.4092322177694 stomach 84.627849529808 98.214231441248 82.7032869316805 testicle 83.7579505126506 89.4524723743191 80.3502177659309 cont.diffExp=5.04177268719135,-2.20891206570788,-7.1492083234424,-12.5201365461158,-8.5057068696116,3.38374862007716,-13.5863819114401,-5.69452186166849 cont.diffExpScore=1.37526723337396 cont.diffExp1.5=0,0,0,0,0,0,0,0 cont.diffExp1.5Score=0 cont.diffExp1.4=0,0,0,0,0,0,0,0 cont.diffExp1.4Score=0 cont.diffExp1.3=0,0,0,0,0,0,0,0 cont.diffExp1.3Score=0 cont.diffExp1.2=0,0,0,0,0,0,0,0 cont.diffExp1.2Score=0 tran.correlation=-0.444142142125314 cont.tran.correlation=0.281404234354780 tran.covariance=-0.00858500370055809 cont.tran.covariance=0.000608153127218174 tran.mean=69.2537751324917 cont.tran.mean=84.4536723009255 weightedLogRatios: wLogRatio Lung -0.14407905960564 cerebhem 2.27574386623212 cortex 2.16184001066435 heart 0.99018921267851 kidney -0.249248501353225 liver 0.103022183630060 stomach 0.59982019797679 testicle 0.277217140342658 cont.weightedLogRatios: wLogRatio Lung 0.273355546966230 cerebhem -0.121309607917265 cortex -0.372744536489197 heart -0.638773328654093 kidney -0.454549013237954 liver 0.183605504751662 stomach -0.67188671738719 testicle -0.293416417021270 varWeightedLogRatios=0.977340564551653 cont.varWeightedLogRatios=0.123607904635938 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.52196822122596 0.0834747060011636 42.1920410378788 2.03076243869424e-225 *** df.mm.trans1 0.677723798508986 0.0713597541949051 9.49728325377799 1.49423010628527e-20 *** df.mm.trans2 0.825156152402616 0.0623281259578536 13.2389052249154 5.08707618392943e-37 *** df.mm.exp2 -0.638368975174032 0.0785429761859918 -8.12763923870619 1.26680884943575e-15 *** df.mm.exp3 -0.462418488737381 0.0785429761859918 -5.88745819412754 5.32703576158609e-09 *** df.mm.exp4 -0.196376679547305 0.0785429761859918 -2.50024494974929 0.0125677254978212 * df.mm.exp5 -0.0573995794446407 0.0785429761859918 -0.730804741963393 0.465067250352871 df.mm.exp6 -0.108387398885123 0.0785429761859918 -1.37997570436418 0.16789830759429 df.mm.exp7 -0.287810059537817 0.0785429761859918 -3.66436406555662 0.000260794440100276 *** df.mm.exp8 -0.148770150960478 0.0785429761859918 -1.89412418760637 0.0584929033456328 . df.mm.trans1:exp2 0.725653007402327 0.07165241333493 10.1274049767222 4.98094155870707e-23 *** df.mm.trans2:exp2 0.145073720263475 0.048726306511268 2.97731822193267 0.00297693069268807 ** df.mm.trans1:exp3 0.637434917925208 0.07165241333493 8.89621002638947 2.60458473190981e-18 *** df.mm.trans2:exp3 0.0974354882769834 0.0487263065112681 1.99964855235747 0.0458046444343283 * df.mm.trans1:exp4 0.226273514810294 0.0716524133349301 3.15793291919712 0.00163587273198188 ** df.mm.trans2:exp4 -0.0394093531453284 0.048726306511268 -0.808790075977027 0.418825626155154 df.mm.trans1:exp5 -0.0555931212238709 0.0716524133349301 -0.775872278914151 0.438005320372881 df.mm.trans2:exp5 -0.0301224780622117 0.0487263065112681 -0.618197442386605 0.53658402119746 df.mm.trans1:exp6 -0.0366193537708739 0.0716524133349301 -0.511069370402102 0.609413737536764 df.mm.trans2:exp6 -0.0942833344886405 0.0487263065112681 -1.93495754632741 0.053273343884281 . df.mm.trans1:exp7 0.168297798298333 0.0716524133349301 2.3488085113288 0.0190247778310505 * df.mm.trans2:exp7 -0.00924880577411097 0.048726306511268 -0.189811344965623 0.849494954482083 df.mm.trans1:exp8 0.0117275604421713 0.0716524133349301 0.163672930140571 0.870021244576245 df.mm.trans2:exp8 -0.0877600531398546 0.0487263065112681 -1.80108158043048 0.0719870365537455 . df.mm.trans1:probe2 -0.152756281047622 0.0533484734687172 -2.86336742394693 0.00427799791471973 ** df.mm.trans1:probe3 -0.0239916545070123 0.0533484734687172 -0.449715857775773 0.6530114508935 df.mm.trans1:probe4 -0.138633533194062 0.0533484734687172 -2.59864105156363 0.00949518228943724 ** df.mm.trans1:probe5 -0.161117918883918 0.0533484734687172 -3.02010363948643 0.00259017765934210 ** df.mm.trans1:probe6 0.785842311411528 0.0533484734687172 14.7303617201406 1.19427180580269e-44 *** df.mm.trans1:probe7 0.049372615731999 0.0533484734687172 0.925473823744 0.354939691598776 df.mm.trans1:probe8 -0.0140668806998153 0.0533484734687172 -0.263679160530505 0.792080729066607 df.mm.trans1:probe9 0.628620909273575 0.0533484734687172 11.7832970355223 3.96774528547708e-30 *** df.mm.trans1:probe10 0.66967432438624 0.0533484734687172 12.5528301157282 1.06371886249560e-33 *** df.mm.trans1:probe11 0.417720747730947 0.0533484734687172 7.83004124712008 1.22397200970033e-14 *** df.mm.trans1:probe12 0.377518719987539 0.0533484734687172 7.076467149691 2.7558280101217e-12 *** df.mm.trans1:probe13 0.263481457500770 0.0533484734687172 4.93887529237873 9.1847602945719e-07 *** df.mm.trans1:probe14 0.409353770716303 0.0533484734687172 7.67320495039736 3.92865954084219e-14 *** df.mm.trans1:probe15 0.285446714348543 0.0533484734687172 5.35060697689737 1.08369040844256e-07 *** df.mm.trans1:probe16 0.364896863982484 0.0533484734687172 6.83987451293155 1.36823557458663e-11 *** df.mm.trans1:probe17 0.151425712589826 0.0533484734687172 2.83842634557518 0.00462412904901311 ** df.mm.trans1:probe18 0.313088192244038 0.0533484734687172 5.86873760179152 5.94248989358824e-09 *** df.mm.trans1:probe19 0.430091221884975 0.0533484734687172 8.06192181182418 2.10344079439182e-15 *** df.mm.trans1:probe20 0.363085730695245 0.0533484734687172 6.8059254011861 1.71523467718917e-11 *** df.mm.trans1:probe21 0.328893261248815 0.0533484734687172 6.16499854380414 1.01602887166505e-09 *** df.mm.trans1:probe22 0.235987043608533 0.0533484734687172 4.4235013349897 1.07605364097822e-05 *** df.mm.trans2:probe2 0.09724542655002 0.0533484734687172 1.82283428610274 0.0686228541679172 . df.mm.trans2:probe3 0.259292060449034 0.0533484734687172 4.86034639025013 1.35711586222471e-06 *** df.mm.trans2:probe4 0.176720186351519 0.0533484734687172 3.31256313182317 0.00095711042992311 *** df.mm.trans2:probe5 0.0986112590122553 0.0533484734687172 1.84843637691113 0.0648302365236219 . df.mm.trans2:probe6 0.0304313939770246 0.0533484734687172 0.57042670574012 0.568514694440533 df.mm.trans3:probe2 -0.576181518689832 0.0533484734687172 -10.8003375022098 8.1805151871114e-26 *** df.mm.trans3:probe3 -0.856770746711667 0.0533484734687172 -16.059892458105 6.97811154741409e-52 *** df.mm.trans3:probe4 -0.586941985106931 0.0533484734687172 -11.0020389890089 1.12454230544298e-26 *** df.mm.trans3:probe5 -0.177930579545345 0.0533484734687172 -3.33525156347128 0.000883110508604377 *** df.mm.trans3:probe6 -0.726047368356574 0.0533484734687172 -13.6095247183093 7.27418299924109e-39 *** df.mm.trans3:probe7 -0.368970829489748 0.0533484734687172 -6.91623968783488 8.19967138440416e-12 *** df.mm.trans3:probe8 -1.06192454858066 0.0533484734687172 -19.9054345801170 1.10971693585896e-74 *** df.mm.trans3:probe9 -0.707595583549484 0.0533484734687172 -13.2636519386896 3.84053470162071e-37 *** df.mm.trans3:probe10 -0.261874508102486 0.0533484734687172 -4.90875354204925 1.06754615677086e-06 *** df.mm.trans3:probe11 -0.933941621859028 0.0533484734687172 -17.5064357259759 3.67764695836938e-60 *** df.mm.trans3:probe12 -0.653127327305957 0.0533484734687172 -12.2426619702425 3.06412202920314e-32 *** df.mm.trans3:probe13 -0.569972935058665 0.0533484734687172 -10.6839595961989 2.537378234955e-25 *** df.mm.trans3:probe14 -0.424801529996529 0.0533484734687172 -7.96276823638874 4.49067497842356e-15 *** df.mm.trans3:probe15 -0.367991507316897 0.0533484734687172 -6.89788260825648 9.27782666790412e-12 *** df.mm.trans3:probe16 -0.340077715757519 0.0533484734687172 -6.37464755119817 2.77990735238309e-10 *** df.mm.trans3:probe17 -0.363921421343414 0.0533484734687172 -6.8215901539678 1.54554788758908e-11 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.39200746196045 0.157701213443528 27.8501817840052 3.08860679338163e-127 *** df.mm.trans1 0.00664412273938072 0.134813530549141 0.0492837974965642 0.96070283706926 df.mm.trans2 -0.0174347821194575 0.117750892049593 -0.148064968476965 0.882320933051177 df.mm.exp2 -0.0146845971031492 0.148384142279271 -0.098963385693274 0.92118690132766 df.mm.exp3 0.122691857236451 0.148384142279271 0.826852892444089 0.408514972828923 df.mm.exp4 0.105171999062374 0.148384142279271 0.708781932131479 0.478622726826968 df.mm.exp5 -0.0546495092111864 0.148384142279271 -0.368297503841963 0.712728285619546 df.mm.exp6 -0.00783622168706532 0.148384142279271 -0.0528103715578777 0.957893399599019 df.mm.exp7 0.188630132563850 0.148384142279271 1.27122837835887 0.203938940349898 df.mm.exp8 0.113718692665183 0.148384142279271 0.766380361933518 0.443628387626459 df.mm.trans1:exp2 -0.0467172727838885 0.13536642499727 -0.345117135100750 0.730077886353798 df.mm.trans2:exp2 0.0431838827077567 0.092054204579542 0.469113636959868 0.639089256615397 df.mm.trans1:exp3 -0.145321479216381 0.13536642499727 -1.07354153158224 0.283283620461496 df.mm.trans2:exp3 0.000723122465134086 0.092054204579542 0.0078553985495497 0.993733908383965 df.mm.trans1:exp4 -0.130055456524631 0.13536642499727 -0.960765984085448 0.336898884103999 df.mm.trans2:exp4 0.0749572427834757 0.092054204579542 0.814272885479194 0.415679820890602 df.mm.trans1:exp5 -0.00961733482004317 0.13536642499727 -0.0710466780831149 0.943374615087616 df.mm.trans2:exp5 0.155571987013463 0.092054204579542 1.69000414184272 0.0913345322649862 . df.mm.trans1:exp6 -0.00327768909384502 0.13536642499727 -0.0242134568738970 0.980687108253616 df.mm.trans2:exp6 0.0171343449487816 0.092054204579542 0.186133213871575 0.852377524949411 df.mm.trans1:exp7 -0.176524404087031 0.13536642499727 -1.30404865231974 0.192512936464859 df.mm.trans2:exp7 0.0345594158982074 0.092054204579542 0.375424632215961 0.707423205465316 df.mm.trans1:exp8 -0.111945269595051 0.13536642499727 -0.826979582250977 0.408443194208507 df.mm.trans2:exp8 0.0160271772178348 0.092054204579542 0.174105868287483 0.861817014030049 df.mm.trans1:probe2 -0.0131649684422893 0.100786446630423 -0.130622408889603 0.896099923725148 df.mm.trans1:probe3 0.0899410091911344 0.100786446630423 0.892391905837713 0.372394629752191 df.mm.trans1:probe4 0.119590657367292 0.100786446630423 1.18657479617098 0.235673313102834 df.mm.trans1:probe5 0.0377737251484136 0.100786446630423 0.374789730279183 0.707895222675316 df.mm.trans1:probe6 0.0672189152467602 0.100786446630423 0.666943993900759 0.504959639410352 df.mm.trans1:probe7 0.157285114553437 0.100786446630423 1.56057803218512 0.118935374112184 df.mm.trans1:probe8 -0.0231470820291169 0.100786446630423 -0.229664630542990 0.818398699071614 df.mm.trans1:probe9 0.0184203287108953 0.100786446630423 0.182765930606139 0.855018215872582 df.mm.trans1:probe10 -0.0197870060260944 0.100786446630423 -0.196326060572925 0.844394303611463 df.mm.trans1:probe11 0.0901819189116459 0.100786446630423 0.894782204618608 0.371115864398865 df.mm.trans1:probe12 0.0157304709676021 0.100786446630423 0.156077245438413 0.876003200392237 df.mm.trans1:probe13 -0.0199726660018503 0.100786446630423 -0.198168173098598 0.842953209010731 df.mm.trans1:probe14 0.233157982991287 0.100786446630423 2.31338628145370 0.0209007109757267 * df.mm.trans1:probe15 0.170997336008976 0.100786446630423 1.6966302685123 0.0900734936566876 . df.mm.trans1:probe16 0.0842217469065451 0.100786446630423 0.835645562695351 0.403551185735316 df.mm.trans1:probe17 0.0552313670652808 0.100786446630423 0.548003912349547 0.583809828758131 df.mm.trans1:probe18 0.0353443548840405 0.100786446630423 0.350685593804550 0.725897074220308 df.mm.trans1:probe19 0.00417665201647282 0.100786446630423 0.0414406118690571 0.96695279505965 df.mm.trans1:probe20 -0.105142724272284 0.100786446630423 -1.04322285175739 0.297093737684184 df.mm.trans1:probe21 0.0729189350802823 0.100786446630423 0.723499414039973 0.469539976790514 df.mm.trans1:probe22 0.00176143875126480 0.100786446630423 0.0174769407014007 0.98605956680472 df.mm.trans2:probe2 0.0172123915099300 0.100786446630423 0.170780815133275 0.864430185258795 df.mm.trans2:probe3 -0.0405020570909882 0.100786446630423 -0.401860155259827 0.687871632490274 df.mm.trans2:probe4 -0.172717916728015 0.100786446630423 -1.71370181708419 0.0868891329443517 . df.mm.trans2:probe5 -0.0715837625407291 0.100786446630423 -0.710251873480783 0.477711267466203 df.mm.trans2:probe6 0.0235360352820157 0.100786446630423 0.233523812664223 0.815401814996792 df.mm.trans3:probe2 0.0412406243040755 0.100786446630423 0.409188196259185 0.68248796890378 df.mm.trans3:probe3 -0.0620944987281242 0.100786446630423 -0.616099692013354 0.537966999429669 df.mm.trans3:probe4 -0.118677394172941 0.100786446630423 -1.17751342705951 0.239266939876854 df.mm.trans3:probe5 -0.0720799391152771 0.100786446630423 -0.715174922076468 0.474665592426108 df.mm.trans3:probe6 0.0306566714431913 0.100786446630423 0.304174543980175 0.761057326454394 df.mm.trans3:probe7 0.0192079405237884 0.100786446630423 0.190580590604831 0.848892346030009 df.mm.trans3:probe8 -0.0637245840653085 0.100786446630423 -0.632273348211015 0.527350809981355 df.mm.trans3:probe9 0.0427217044468101 0.100786446630423 0.423883427535326 0.671740733685253 df.mm.trans3:probe10 0.0831062338923917 0.100786446630423 0.824577477139722 0.409805434850348 df.mm.trans3:probe11 0.0855272018821851 0.100786446630423 0.84859824650637 0.396305162449521 df.mm.trans3:probe12 0.0254248163845402 0.100786446630423 0.252264240228363 0.800887949635549 df.mm.trans3:probe13 -0.162370556579805 0.100786446630423 -1.61103563036811 0.107483167003370 df.mm.trans3:probe14 0.038071854047672 0.100786446630423 0.377747755978329 0.70569704235859 df.mm.trans3:probe15 -0.0724107896142931 0.100786446630423 -0.718457610474335 0.47264068579577 df.mm.trans3:probe16 0.0176421669550061 0.100786446630423 0.175045033780173 0.861079193450377 df.mm.trans3:probe17 -0.0468256596203378 0.100786446630423 -0.464602743581626 0.642315707132292